Being able to see and measure a real world scene at the same time on a computer screen is a natural desire of human being and also the need in many applications. The purpose of making a unified spectral and geospatial information model is to provide an effective and efficient foundation data layer and representation to the building of a geo-referenced 3D ground surface model. Such a geo-referenced 3D ground surface model allows the viewing and measuring of the ground surface of the real world from images of the models displayed on a computer screen in 3D.
There are various methods to model and present the real world ground surface in 3D and each method determines its way of how and in what format the data are to be represented and used. The representation of the 3D information plays the key role in any ground surface modeling method and can make huge differences among the methods in effectiveness and efficiency to present the 3D real world.
In the past, a lot of researches and developments were conducted and a number of methods were developed for 3D ground surface modeling. In all commonly used methods, all of them take a common approach, which at present time acts like the “standard way”, to create 3D ground surface models in the geospatial information industry. This “standard way” is to first collect and create 3D vector frame structures of ground objects (mainly buildings) in certain format by conventional photogrammetric processes and then attach walls or facets to the buildings by manual cut and paste process from pictures of the buildings taken either on the ground or from aerial oblique imagery. In nature these methods are vector-based methods. Although the 3D buildings created in this way normally look good, they are not fully geo-referenced in the real world coordinate system, i.e., they either have no real world coordinates or they only allow one Z for each XY, which can not correctly represent many objects on ground surface, especially building facets. Further, most of the buildings collected look unreal and the buildings that were not collected for various reasons (such as cost) and other ground objects, such as trees will look badly distorted and most likely lying on the ground. In general, 3D ground surface models created in such approach only look good on those buildings that were collected and look bad for those not collected. Additionally, the entire process to produce such a 3D ground surface model is very time consuming and labor intensive, particularly for the making of building facets, which therefore limits its use mainly only to the displaying of downtown areas in big cities.
In the last decade, many advancements in remote sensing technologies have created the necessary material conditions for the development of this invention, particularly the availability of the direct observation and measurement capability by Global Positioning System (GPS) for position, the Inertial Measurement Unit (IMU) for attitudes, Light Detection And Ranging (LIDAR) for high quality ground surface elevation or range data acquisition, and airborne digital oblique imagery acquisition camera system.
The direct and accurate observation of positions and attitudes from GPS and IMU respectively allows the direct exterior orientation determination for airborne oblique imagery, where the exterior orientation consists of positions and attitudes. In order to link an image to a common ground coordinate system, one has to know the six parameter exterior orientation of the image: i.e., the XYZ coordinates of the image exposure center for position and the three angles of the image exposure center in relation to the ground coordinate system for attitude both at the time of exposure. Conventionally, the determination of exterior orientation of airborne imagery, oblique or vertical imagery, is made through an aerial triangulation process, which would need ground control points and is very difficult to obtain accurate and reliable result for oblique imagery because of its oblique nature. With the direct and accurate observations of positions and attitudes for each and every image, there is no need to do aerial triangulation any more.
The LIDAR technology represents today's best way to acquire ground surface elevation or range data with high accuracy, high density, and high consistency in the quality for a large area in relatively short time. The ground surface elevation or range data collected by a LIDAR system cannot be easily, if can at all, matched by the today's conventional photogrammetric processes. Comparing the data produced by conventional photogrammetric processes with the data produced by LIDAR, photogrammetric data only include major or large size objects such as buildings, roads and major terrain elevation formations and changes, whereas LIDAR data includes everything of the ground surface without any discrimination for type and size of the objects of the ground surface.
People have been acquiring and using airborne oblique imagery for decades, mainly with film metric cameras. Here, an oblique image is one taken with the axis of the camera lens intentionally directed between the horizontal and the vertical and when the axis of the camera lens is set as nearly vertical, then the image taken is a vertical image (American Society of Photogrammetry and Remote Sensing. Manual of Photogrammetry, 4th Edition, pp 279-280. Falls Church, Va.: ASPRS. 1980). In recent years, more and more multiple digital cameras, such as five-camera systems, are to be used to acquire oblique imagery. The great increase in the utilization of oblique imagery is mainly attributed to direct observation of exterior orientation parameters of imagery from GPS and IMU. The multiple camera oblique imaging system can quickly acquire imagery for a large area with high ground pixel resolution and image quality for ground object facets, especially for building facets.
The data acquired by using these technologies provides the necessary materials and conditions to create unified spectral and geospatial information model and in turn to build an effective and efficient geo-referenced 3D ground surface model of the real world by the method and system of this invention. Besides being the foundation data for a geo-referenced 3D ground surface model, the unified spectral and geospatial information model can and should also serve as a foundational layer in the Geographic Information Systems (GIS). Currently, a typical GIS has a layer of geo-referenced two-dimensional (2D) orthophoto. Although on a 2D orthophoto, one can make many measurements, all the measurements are limited to 2D, i.e., only in XY plane, no third dimensional information available. In such a GIS, the world is only 2 dimensional. Having the unified spectral and geospatial information model in a GIS will add one dimension to the image layer of a GIS and greatly expand the use of airborne imagery beyond the traditional professional users. The addition of the third dimension to the image layer of a GIS will make the mostly 2D vector-based GISs be capable to handle 3D image information as well.